There are commercially available products to analyze entities. For example, SAP Americas™ offers a product known as ThingFinder™. ThingFinder™ processes a stream of data to identify entities and potential relationships between them. In this context, an entity (or entity mention) is an object (e.g., a word or group of related words) in a data set or ordered data set. The data set may comprise a set of files, internet chat communications, email strings and the like. The entities are analyzed to derive information, such as a data summary, customer sentiment, customer preferences, and related forms of Business Intelligence.
Entity analysis is computationally expensive. Some of the computational expense is attributable to the need for multiple processing passes over an entity to ascertain entity relationships. More particularly, with existing techniques, rule based processing results in multiple processing passes of an entity before it can be assigned to a group of related entities.
It would be desirable to provide improved techniques for analyzing entities. In particular, it would be desirable to provide improved entity processing performance with reduced computational load.